Occupational health impact of the 2009 H1N1 flu pandemic: surveillance of sickness absence.
Identifieur interne : 000312 ( Main/Exploration ); précédent : 000311; suivant : 000313Occupational health impact of the 2009 H1N1 flu pandemic: surveillance of sickness absence.
Auteurs : Isabel Torá-Rocamora [Espagne] ; George L. Delclos ; José Miguel Martínez ; Josefina Jardí ; Constança Alberti ; Rafael Manzanera ; Yutaka Yasui ; Ram N Clèries ; Aurelio Tobías ; Fernando G. BenavidesSource :
- Occupational and environmental medicine [ 1470-7926 ] ; 2012.
Descripteurs français
- KwdFr :
- Adulte (MeSH), Adulte d'âge moyen (MeSH), Congé maladie (statistiques et données numériques), Espagne (épidémiologie), Facteurs de risque (MeSH), Femelle (MeSH), Grippe humaine (épidémiologie), Humains (MeSH), Incidence (MeSH), Mâle (MeSH), Pandémies (statistiques et données numériques), Sous-type H1N1 du virus de la grippe A (MeSH), Sujet âgé (MeSH), Surveillance de la population (méthodes).
- MESH :
- méthodes : Surveillance de la population.
- statistiques et données numériques : Congé maladie, Pandémies.
- épidémiologie : Espagne, Grippe humaine.
- Adulte, Adulte d'âge moyen, Facteurs de risque, Femelle, Humains, Incidence, Mâle, Sous-type H1N1 du virus de la grippe A, Sujet âgé.
- Wicri :
- geographic : Espagne.
English descriptors
- KwdEn :
- Adult (MeSH), Aged (MeSH), Female (MeSH), Humans (MeSH), Incidence (MeSH), Influenza A Virus, H1N1 Subtype (MeSH), Influenza, Human (epidemiology), Male (MeSH), Middle Aged (MeSH), Pandemics (statistics & numerical data), Population Surveillance (methods), Risk Factors (MeSH), Sick Leave (statistics & numerical data), Spain (epidemiology).
- MESH :
- geographic , epidemiology : Spain.
- epidemiology : Influenza, Human.
- methods : Population Surveillance.
- statistics & numerical data : Pandemics, Sick Leave.
- Adult, Aged, Female, Humans, Incidence, Influenza A Virus, H1N1 Subtype, Male, Middle Aged, Risk Factors.
Abstract
OBJECTIVES
Workplace absences due to illness can disrupt usual operations and increase costs for businesses. This study of sickness absence due to influenza and influenza-related illness presents a unique opportunity to characterise and measure the impact of the 2009 (H1N1) pandemic, by comparing trends during the pandemic to those of previous years, and adding this information to that obtained by traditional epidemiological surveillance systems.
METHODS
We compared the numbers of cases of sickness absence due to illness caused by influenza and influenza-related illness in 2007-2009, and in the first 3 months of 2010 in Catalonia (n=811 940) using a time series approach. Trends were examined by economic activity, age and gender. The weekly endemic-epidemic index (EEI) was calculated and its 95% CI obtained with the delta method, with observed and expected cases considered as independent random variables.
RESULTS
Influenza activity peaked earlier in 2009 and yielded more cases than in previous years. Week 46 (in November 2009) had the highest number of new cases resulting in sickness absence (EEI 20.99; 95% CI 9.44 to 46.69). Women and the 'education, health and other social activities' sector were the most affected.
CONCLUSIONS
Results indicate that the new H1N1 pandemic had a significant impact on business, with shifts in the timing of peak incidence, a doubling in the number of cases, and changes in the distribution of cases by economic activity sector and gender. Traditional epidemiological surveillance systems could benefit from the addition of information based on sickness absence data.
DOI: 10.1136/oem.2011.065003
PubMed: 21676949
Affiliations:
Links toward previous steps (curation, corpus...)
Le document en format XML
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<author><name sortKey="Delclos, George L" sort="Delclos, George L" uniqKey="Delclos G" first="George L" last="Delclos">George L. Delclos</name>
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<author><name sortKey="Martinez, Jose Miguel" sort="Martinez, Jose Miguel" uniqKey="Martinez J" first="José Miguel" last="Martínez">José Miguel Martínez</name>
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<author><name sortKey="Jardi, Josefina" sort="Jardi, Josefina" uniqKey="Jardi J" first="Josefina" last="Jardí">Josefina Jardí</name>
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<author><name sortKey="Alberti, Constanca" sort="Alberti, Constanca" uniqKey="Alberti C" first="Constança" last="Alberti">Constança Alberti</name>
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<author><name sortKey="Manzanera, Rafael" sort="Manzanera, Rafael" uniqKey="Manzanera R" first="Rafael" last="Manzanera">Rafael Manzanera</name>
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<author><name sortKey="Cleries, Ram N" sort="Cleries, Ram N" uniqKey="Cleries R" first="Ram N" last="Clèries">Ram N Clèries</name>
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<author><name sortKey="Tobias, Aurelio" sort="Tobias, Aurelio" uniqKey="Tobias A" first="Aurelio" last="Tobías">Aurelio Tobías</name>
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<profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>Adult (MeSH)</term>
<term>Aged (MeSH)</term>
<term>Female (MeSH)</term>
<term>Humans (MeSH)</term>
<term>Incidence (MeSH)</term>
<term>Influenza A Virus, H1N1 Subtype (MeSH)</term>
<term>Influenza, Human (epidemiology)</term>
<term>Male (MeSH)</term>
<term>Middle Aged (MeSH)</term>
<term>Pandemics (statistics & numerical data)</term>
<term>Population Surveillance (methods)</term>
<term>Risk Factors (MeSH)</term>
<term>Sick Leave (statistics & numerical data)</term>
<term>Spain (epidemiology)</term>
</keywords>
<keywords scheme="KwdFr" xml:lang="fr"><term>Adulte (MeSH)</term>
<term>Adulte d'âge moyen (MeSH)</term>
<term>Congé maladie (statistiques et données numériques)</term>
<term>Espagne (épidémiologie)</term>
<term>Facteurs de risque (MeSH)</term>
<term>Femelle (MeSH)</term>
<term>Grippe humaine (épidémiologie)</term>
<term>Humains (MeSH)</term>
<term>Incidence (MeSH)</term>
<term>Mâle (MeSH)</term>
<term>Pandémies (statistiques et données numériques)</term>
<term>Sous-type H1N1 du virus de la grippe A (MeSH)</term>
<term>Sujet âgé (MeSH)</term>
<term>Surveillance de la population (méthodes)</term>
</keywords>
<keywords scheme="MESH" type="geographic" qualifier="epidemiology" xml:lang="en"><term>Spain</term>
</keywords>
<keywords scheme="MESH" qualifier="epidemiology" xml:lang="en"><term>Influenza, Human</term>
</keywords>
<keywords scheme="MESH" qualifier="methods" xml:lang="en"><term>Population Surveillance</term>
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<keywords scheme="MESH" qualifier="méthodes" xml:lang="fr"><term>Surveillance de la population</term>
</keywords>
<keywords scheme="MESH" qualifier="statistics & numerical data" xml:lang="en"><term>Pandemics</term>
<term>Sick Leave</term>
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<keywords scheme="MESH" qualifier="statistiques et données numériques" xml:lang="fr"><term>Congé maladie</term>
<term>Pandémies</term>
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<keywords scheme="MESH" qualifier="épidémiologie" xml:lang="fr"><term>Espagne</term>
<term>Grippe humaine</term>
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<keywords scheme="MESH" xml:lang="en"><term>Adult</term>
<term>Aged</term>
<term>Female</term>
<term>Humans</term>
<term>Incidence</term>
<term>Influenza A Virus, H1N1 Subtype</term>
<term>Male</term>
<term>Middle Aged</term>
<term>Risk Factors</term>
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<keywords scheme="MESH" xml:lang="fr"><term>Adulte</term>
<term>Adulte d'âge moyen</term>
<term>Facteurs de risque</term>
<term>Femelle</term>
<term>Humains</term>
<term>Incidence</term>
<term>Mâle</term>
<term>Sous-type H1N1 du virus de la grippe A</term>
<term>Sujet âgé</term>
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<front><div type="abstract" xml:lang="en"><p><b>OBJECTIVES</b>
</p>
<p>Workplace absences due to illness can disrupt usual operations and increase costs for businesses. This study of sickness absence due to influenza and influenza-related illness presents a unique opportunity to characterise and measure the impact of the 2009 (H1N1) pandemic, by comparing trends during the pandemic to those of previous years, and adding this information to that obtained by traditional epidemiological surveillance systems.</p>
</div>
<div type="abstract" xml:lang="en"><p><b>METHODS</b>
</p>
<p>We compared the numbers of cases of sickness absence due to illness caused by influenza and influenza-related illness in 2007-2009, and in the first 3 months of 2010 in Catalonia (n=811 940) using a time series approach. Trends were examined by economic activity, age and gender. The weekly endemic-epidemic index (EEI) was calculated and its 95% CI obtained with the delta method, with observed and expected cases considered as independent random variables.</p>
</div>
<div type="abstract" xml:lang="en"><p><b>RESULTS</b>
</p>
<p>Influenza activity peaked earlier in 2009 and yielded more cases than in previous years. Week 46 (in November 2009) had the highest number of new cases resulting in sickness absence (EEI 20.99; 95% CI 9.44 to 46.69). Women and the 'education, health and other social activities' sector were the most affected.</p>
</div>
<div type="abstract" xml:lang="en"><p><b>CONCLUSIONS</b>
</p>
<p>Results indicate that the new H1N1 pandemic had a significant impact on business, with shifts in the timing of peak incidence, a doubling in the number of cases, and changes in the distribution of cases by economic activity sector and gender. Traditional epidemiological surveillance systems could benefit from the addition of information based on sickness absence data.</p>
</div>
</front>
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<Abstract><AbstractText Label="OBJECTIVES" NlmCategory="OBJECTIVE">Workplace absences due to illness can disrupt usual operations and increase costs for businesses. This study of sickness absence due to influenza and influenza-related illness presents a unique opportunity to characterise and measure the impact of the 2009 (H1N1) pandemic, by comparing trends during the pandemic to those of previous years, and adding this information to that obtained by traditional epidemiological surveillance systems.</AbstractText>
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<AbstractText Label="RESULTS" NlmCategory="RESULTS">Influenza activity peaked earlier in 2009 and yielded more cases than in previous years. Week 46 (in November 2009) had the highest number of new cases resulting in sickness absence (EEI 20.99; 95% CI 9.44 to 46.69). Women and the 'education, health and other social activities' sector were the most affected.</AbstractText>
<AbstractText Label="CONCLUSIONS" NlmCategory="CONCLUSIONS">Results indicate that the new H1N1 pandemic had a significant impact on business, with shifts in the timing of peak incidence, a doubling in the number of cases, and changes in the distribution of cases by economic activity sector and gender. Traditional epidemiological surveillance systems could benefit from the addition of information based on sickness absence data.</AbstractText>
</Abstract>
<AuthorList CompleteYN="Y"><Author ValidYN="Y"><LastName>Torá-Rocamora</LastName>
<ForeName>Isabel</ForeName>
<Initials>I</Initials>
<AffiliationInfo><Affiliation>Department of Experimental and Health Sciences, Center for Research in Occupational Health (CiSAL), Pompeu Fabra University, Barcelona, Spain.</Affiliation>
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<Author ValidYN="Y"><LastName>Delclos</LastName>
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<Author ValidYN="Y"><LastName>Martínez</LastName>
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<Author ValidYN="Y"><LastName>Jardí</LastName>
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<Author ValidYN="Y"><LastName>Alberti</LastName>
<ForeName>Constança</ForeName>
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<Author ValidYN="Y"><LastName>Manzanera</LastName>
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<Author ValidYN="Y"><LastName>Clèries</LastName>
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<Author ValidYN="Y"><LastName>Tobías</LastName>
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<name sortKey="Cleries, Ram N" sort="Cleries, Ram N" uniqKey="Cleries R" first="Ram N" last="Clèries">Ram N Clèries</name>
<name sortKey="Delclos, George L" sort="Delclos, George L" uniqKey="Delclos G" first="George L" last="Delclos">George L. Delclos</name>
<name sortKey="Jardi, Josefina" sort="Jardi, Josefina" uniqKey="Jardi J" first="Josefina" last="Jardí">Josefina Jardí</name>
<name sortKey="Manzanera, Rafael" sort="Manzanera, Rafael" uniqKey="Manzanera R" first="Rafael" last="Manzanera">Rafael Manzanera</name>
<name sortKey="Martinez, Jose Miguel" sort="Martinez, Jose Miguel" uniqKey="Martinez J" first="José Miguel" last="Martínez">José Miguel Martínez</name>
<name sortKey="Tobias, Aurelio" sort="Tobias, Aurelio" uniqKey="Tobias A" first="Aurelio" last="Tobías">Aurelio Tobías</name>
<name sortKey="Yasui, Yutaka" sort="Yasui, Yutaka" uniqKey="Yasui Y" first="Yutaka" last="Yasui">Yutaka Yasui</name>
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<country name="Espagne"><region name="Catalogne"><name sortKey="Tora Rocamora, Isabel" sort="Tora Rocamora, Isabel" uniqKey="Tora Rocamora I" first="Isabel" last="Torá-Rocamora">Isabel Torá-Rocamora</name>
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